Technology can improve implementation strategies' efficiency, simplifying progress tracking and removing distance-related barriers. However, incorporating technology is meaningful only if the resulting strategy is usable and useful. Hence, we must systematically assess technological strategies' usability and usefulness before employing them. Our objective was therefore to adapt the effort-vs-impact assessment (commonly used in systems science and operations planning) to decision-making for technological implementation strategies. The approach includes three components - assessing the effort needed to make a technological implementation strategy usable, assessing its impact (i.e., usefulness regarding performance/efficiency/quality), and deciding whether/how to use it. The approach generates a two-by-two effort-vs-impact chart that categorizes the strategy by effort (little/much) and impact (small/large), which serves as a guide for deciding whether/how to use the strategy. We provide a case study of applying this approach to design a package of technological strategies for implementing a 5 A's tobacco cessation intervention at a Federally Qualified Health Center. The effort-vs-impact chart guides stakeholder-involved decision-making around considered technologies. Specification of less technological alternatives helps tailor each technological strategy within the package (minimizing the effort needed to make the strategy usable while maximizing its usefulness), aligning to organizational priorities and clinical tasks. Our three-component approach enables methodical and documentable assessments of whether/how to use a technological implementation strategy, building on stakeholder-involved perceptions of its usability and usefulness. As technology advances, results of effort-vs-impact assessments will likely also change. Thus, even for a single technological implementation strategy, the three-component approach can be repeatedly applied to guide implementation in dynamic contexts.Opioid analgesics and maintenance treatments, benzodiazepines and z-drugs, and other sedatives and stimulants are increasingly being abused to induce psychoactive effects or alter the effects of other drugs, eventually leading to dependence. Awareness of prescription drug abuse has been increasing in the last two decades, and organizations such as the International Narcotics Control Board has predicted that, worldwide, prescription drug abuse may exceed the use of illicit drugs. https://www.selleckchem.com/products/nvp-dky709.html Assessment of prescription drug abuse tackles an issue that is hidden by nature, which therefore requires a specific monitoring. The current best practice is to use multiple detection systems to assess prescription drug abuse by various populations in a timely, sensitive, and specific manner. In the early 2000's, we designed a method to detect and quantify doctor shopping for prescription drugs from the French National Health Data System, which is one of the world's largest claims database, and a first-class data source for pharmacoeperal pharmacological classes (e.g., opioids, benzodiazepines, antidepressants, and methylphenidate).People with autism spectrum disorder (ASD) exhibit atypicality in various domains of behavior. Previous psychophysiological studies have revealed an atypical pattern of autonomic nervous system (ANS) activation induced by psychosocial stimulation. Thus, it might be feasible to develop a novel assessment tool to evaluate the risk of ASD by measuring ANS activation in response to emotional stimulation. The present study investigated whether people with ASD could be automatically classified from neurotypical adults based solely on physiological data obtained by the recently introduced non-contact measurement of pulse wave. We video-recorded faces of adult males with and without ASD while watching emotion-inducing video clips. Features reflective of ANS activation were extracted from the temporal fluctuation of facial skin coloration and entered into a machine-learning algorithm. Though the performance was modest, the gradient boosting classifier succeeded in classifying people with and without ASD, which indicates that facial skin color fluctuation contains information useful for detecting people with ASD. Taking into consideration the fact that the current study recruited only high-functioning adults who have relatively mild symptoms and probably developed some compensatory strategies, ASD screening by non-contact measurement of pulse wave could be a promising assessment tool to evaluate ASD risk.Background The Risk of Suicide Protocol (RoSP) is a structured professional judgment (SPJ) scheme designed in line with NICE guidelines to improve clinicians' ability to evaluate and manage suicide risk. Aims This study aimed to evaluate the efficacy of RoSP in two settings (1) unexpected deaths of people in the community who were known to mental health services; and (2) an inpatient hospital specializing in the assessment and treatment of patients with personality disorder. Method In Study 1, information from a database of unexpected deaths (N = 68) within an NHS health board was used to complete a RoSP assessment (blind to cause of death) and information from the Coroner's Court was used to assign people to suicide vs. natural causes/accidental death. In Study 2, patients (N = 62) were assessed on the RoSP upon admission to hospital and their self-injurious behaviors were recorded over the first 3 months of admission. Results (1) Evaluations using RoSP were highly reliable in both samples (ICCs 0.93-0.98); (2) professional judgment based on the RoSP was predictive of completed suicide in the community sample (AUC = 0.83) and; (3) was predictive of both suicide attempts (AUC = 0.81) and all self-injurious behaviors (AUC = 0.80) for the inpatient sample. Conclusion RoSP is a reliable and valid instrument for the structured clinical evaluation of suicide risk for use in inpatient psychiatric services and in community mental health services. RoSP's efficacy is comparable to well-established structured professional judgment instruments designed to predict other risk behavior (e.g., HCR-20 and the prediction of violence). The use of RoSP for the clinical evaluation of suicide risk and safety-planning provides a structure for meeting NICE guidelines for suicide prevention and is now evidence-based.